Through-the-wall radar detection using machine learning

被引：9

作者：

Wood, Aihua ^{[1
]}

Wood, Ryan ^{[2
]}

Charnley, Matthew ^{[3
]}

机构：

[1] Air Force Inst Technol, Dept Math & Stat, 2950 Hobson Way, Wright Patterson AFB, OH 45433 USA

[2] Harvard Univ, Dept Stat, Cambridge, MA 02138 USA

[3] Rutgers State Univ, Dept Math, 110 Frelinghuysen Rd, Piscataway, NJ 08854 USA

来源：

RESULTS IN APPLIED MATHEMATICS | 2020年 / 7卷

关键词：

D O I：

10.1016/j.rinam.2020.100106

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

This paper explores the through-the-wall inverse scattering problem via machine learning. The reconstruction method seeks to discover the shape, location, and type of hidden objects behind walls, as well as identifying certain material properties of the targets. We simulate RF sources and receivers placed outside the room to generate observation data with objects randomly placed inside the room. We experiment with two types of neural networks and use an 80-20 train-test split for reconstruction and classification. (C) 2020 The Author(s). Published by Elsevier B.V.

引用

页数：8

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